[AI Image Inspection Case] Assembly Inspection of Wire Harness Work Parts
Detects incorrect assembly of wire harness work parts, missing parts, and surplus assembly of parts!
Harness length: A free simple evaluation was conducted to detect incorrect assembly of work parts (different connector colors, different connector shapes), missing parts, and surplus assembly for lengths of 500 to 1000 mm. In the inspection process, automation is being promoted with the aim of pursuing stable inspection accuracy and reducing costs. As the shortage of personnel due to the aging workforce becomes more pronounced, please consider improving operational efficiency through image inspection to protect "Japanese manufacturing." [Inspection Settings and Results] By creating a simple fixed jig and capturing images within the range that accommodates the entire product, it was possible to distinguish the presence or absence of the O-ring on the bush and the color difference of the semi-lock. It is difficult to detect band or tube missing parts in the overall field of view. While it may be possible to detect them by capturing images individually with magnification, this would increase the number of cameras and inspection cycles. In this case, inspections for "presence" or "absence" and distinguishing between "gray" or "blue" were possible simultaneously in a single learning setup.
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Software Used: DeepSky
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